{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "import random\n",
    "import time\n",
    "import matplotlib.pyplot as plt\n",
    "import math"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "#生成测试数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_length = 10\n",
    "nums = list(range(num_length))\n",
    "nums"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[7, 1, 8, 3, 9]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n = 5\n",
    "select_nums = random.sample(nums, n)\n",
    "select_nums"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 2, 4, 5, 6]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_nums = [element for element in nums if element not in select_nums]\n",
    "new_nums"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "target = random.choice(select_nums)\n",
    "target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "def generate_data(num_length, n):\n",
    "    nums = list(range(num_length))\n",
    "    select_nums = random.sample(nums, n)\n",
    "    new_nums = [element for element in nums if element not in select_nums]\n",
    "    target = random.choice(select_nums)\n",
    "    return new_nums, target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "#二分算法"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "def algorithm(nums, target):\n",
    "    left = 0\n",
    "    right = len(nums) - 1\n",
    "    while left <= right:\n",
    "        middle = left + (right - left)//2\n",
    "        if target < nums[middle]:\n",
    "            right = middle - 1\n",
    "        elif target > nums[middle]:\n",
    "            left = middle + 1 \n",
    "        else:\n",
    "            return middle\n",
    "    return right + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "algorithm(new_nums, target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#序列长度\n",
    "start_length_nums =10\n",
    "end_length_nums =1001\n",
    "length_nums = list(range(start_length_nums, end_length_nums, 10))\n",
    "len(length_nums)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "def measure(algorithm, length_nums):\n",
    "    trial_nums = 20    #每个序列长度测试trail_nums次，算平均运行时间\n",
    "    time_list = []\n",
    "    for length in length_nums:\n",
    "        nums, target = generate_data(length,int(length*0.5))\n",
    "        total_time = 0\n",
    "        for _ in range(trial_nums):\n",
    "            target = random.choice(nums)\n",
    "            start_time = time.perf_counter() \n",
    "            algorithm(nums, target)\n",
    "            end_time = time.perf_counter() \n",
    "            total_time += end_time - start_time\n",
    "        avg_time = total_time / trial_nums\n",
    "        time_list.append(avg_time)\n",
    "    return time_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "#时间复杂度O（logn）\n",
    "o_log = [math.log(num,20)/1000000 for num in length_nums]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制时间复杂度图\n",
    "plt.figure(figsize=(10, 5))\n",
    "plt.plot(length_nums, measure(algorithm, length_nums), label='Algorithm  - Time')\n",
    "plt.plot(length_nums, o_log, label='O(logn)')\n",
    "plt.xlabel('Sequence Length')\n",
    "plt.ylabel('Time (seconds)')\n",
    "plt.title('Time Complexity')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
